My Data is Mine Award – 2024 edition

Data Altruism by Default: An Alternative to Consent for Personal Data Processing in Machine Learning
// WINNER

This paper examines the need for a new framework to balance the development of high-quality AI systems with the protection of personal data. It critiques current data practices, which often involve dubious or unlawful monetization of personal data, misleadingly labeled as data altruism. The author argues that the Data Governance Act's definition of data altruism is too limited to address these issues. The paper proposes a novel approach that allows necessary data processing for AI development while enforcing strict safeguards and objective limitations on business models. This approach aims to provoke societal and political discussion rather than serve as a final solution.